44
2600:Mathematics(比率: 36.8 %)
| DOI | タイトル | 著者 | ジャーナル | 発行年 | 科研費成果論文 |
|---|---|---|---|---|---|
| 10.1007/s00332-018-9525-3 | Machine Learning Approximation Algorithms For High-Dimensional Fully Nonlinear Partial Differential Equations And Second-Order Backward Stochastic Differential Equations | Beck, Christian, 0000-0002-3609-7778; E, Weinan; Jentzen, Arnulf | Journal Of Nonlinear Science | 2019 | NA |
| 10.1007/s00466-019-01740-0 | Prediction Of Aerodynamic Flow Fields Using Convolutional Neural Networks | Bhatnagar, Saakaar; Afshar, Yaser; Pan, Shaowu; Duraisamy, Karthik; Kaushik, Shailendra | Computational Mechanics | 2019 | NA |
| 10.1016/j.cma.2018.07.017 | Reduced Order Modeling For Nonlinear Structural Analysis Using Gaussian Process Regression | Guo, Mengwu, 0000-0002-5541-437X; Hesthaven, Jan S. | Computer Methods In Applied Mechanics And Engineering | 2018 | NA |
| 10.1016/j.cma.2018.10.029 | Data-Driven Reduced Order Modeling For Time-Dependent Problems | Guo, Mengwu, 0000-0002-5541-437X; Hesthaven, Jan S. | Computer Methods In Applied Mechanics And Engineering | 2019 | NA |
| 10.1016/j.cma.2019.112623 | Machine Learning In Cardiovascular Flows Modeling: Predicting Arterial Blood Pressure From Non-Invasive 4D Flow Mri Data Using Physics-Informed Neural Networks | Kissas, Georgios; Yang, Yibo; Hwuang, Eileen; Witschey, Walter R.; Detre, John A.; Perdikaris, Paris, 0000-0002-2816-3229 | Computer Methods In Applied Mechanics And Engineering | 2020 | NA |
| 10.1016/j.cma.2019.112732 | Surrogate Modeling For Fluid Flows Based On Physics-Constrained Deep Learning Without Simulation Data | Sun, Luning; Gao, Han; Pan, Shaowu, 0000-0002-2462-362X; Wang, Jian-Xun, 0000-0002-9030-1733 | Computer Methods In Applied Mechanics And Engineering | 2020 | NA |
| 10.1016/j.cma.2019.112789 | Physics-Informed Neural Networks For High-Speed Flows | Mao, Zhiping; Jagtap, Ameya D.; Karniadakis, George Em | Computer Methods In Applied Mechanics And Engineering | 2020 | NA |
| 10.1016/j.compfluid.2018.07.021 | Projection-Based Model Reduction: Formulations For Physics-Based Machine Learning | Swischuk, Renee; Mainini, Laura, 0000-0002-5969-9069; Peherstorfer, Benjamin; Willcox, Karen | Computers & Fluids | 2019 | NA |
| 10.1016/j.jcp.2018.04.018 | Bayesian Deep Convolutional Encoder<U+2013>Decoder Networks For Surrogate Modeling And Uncertainty Quantification | Zhu, Yinhao; Zabaras, Nicholas | Journal Of Computational Physics | 2018 | NA |
| 10.1016/j.jcp.2018.08.029 | Dgm: A Deep Learning Algorithm For Solving Partial Differential Equations | Sirignano, Justin; Spiliopoulos, Konstantinos | Journal Of Computational Physics | 2018 | NA |
| 10.1016/j.jcp.2018.08.036 | Deep Uq: Learning Deep Neural Network Surrogate Models For High Dimensional Uncertainty Quantification | Tripathy, Rohit K.; Bilionis, Ilias | Journal Of Computational Physics | 2018 | NA |
| 10.1016/j.jcp.2018.10.045 | Physics-Informed Neural Networks: A Deep Learning Framework For Solving Forward And Inverse Problems Involving Nonlinear Partial Differential Equations | Raissi, M., 0000-0002-8467-4568; Perdikaris, P., 0000-0002-2816-3229; Karniadakis, G.E. | Journal Of Computational Physics | 2019 | NA |
| 10.1016/j.jcp.2019.01.031 | Non-Intrusive Reduced Order Modeling Of Unsteady Flows Using Artificial Neural Networks With Application To A Combustion Problem | Wang, Qian, 0000-0001-5409-1663; Hesthaven, Jan S., 0000-0001-8074-1586; Ray, Deep, 0000-0002-8460-9862 | Journal Of Computational Physics | 2019 | NA |
| 10.1016/j.jcp.2019.05.024 | Physics-Constrained Deep Learning For High-Dimensional Surrogate Modeling And Uncertainty Quantification Without Labeled Data | Zhu, Yinhao, 0000-0002-9435-4576; Zabaras, Nicholas, 0000-0003-3144-8388; Koutsourelakis, Phaedon-Stelios, 0000-0002-9345-759X; Perdikaris, Paris, 0000-0002-2816-3229 | Journal Of Computational Physics | 2019 | NA |
| 10.1016/j.jcp.2019.05.027 | Adversarial Uncertainty Quantification In Physics-Informed Neural Networks | Yang, Yibo; Perdikaris, Paris, 0000-0002-2816-3229 | Journal Of Computational Physics | 2019 | NA |
| 10.1016/j.jcp.2019.07.048 | Quantifying Total Uncertainty In Physics-Informed Neural Networks For Solving Forward And Inverse Stochastic Problems | Zhang, Dongkun; Lu, Lu; Guo, Ling; Karniadakis, George Em | Journal Of Computational Physics | 2019 | NA |
| 10.1016/j.jcp.2019.108910 | Deep Neural Networks For Data-Driven Les Closure Models | Beck, Andrea, 0000-0003-3634-7447; Flad, David; Munz, Claus-Dieter | Journal Of Computational Physics | 2019 | NA |
| 10.1016/j.jcp.2019.108925 | Pde-Net 2.0: Learning Pdes From Data With A Numeric-Symbolic Hybrid Deep Network | Long, Zichao; Lu, Yiping; Dong, Bin | Journal Of Computational Physics | 2019 | NA |
| 10.1016/j.jcp.2019.109020 | A Composite Neural Network That Learns From Multi-Fidelity Data: Application To Function Approximation And Inverse Pde Problems | Meng, Xuhui; Karniadakis, George Em | Journal Of Computational Physics | 2020 | NA |
| 10.1016/j.jcp.2019.109136 | Adaptive Activation Functions Accelerate Convergence In Deep And Physics-Informed Neural Networks | Jagtap, Ameya D., 0000-0002-8831-1000; Kawaguchi, Kenji; Karniadakis, George Em | Journal Of Computational Physics | 2020 | NA |
| 10.1016/j.neucom.2018.06.056 | A Unified Deep Artificial Neural Network Approach To Partial Differential Equations In Complex Geometries | Berg, Jens, 0000-0003-3008-8915; Nystrom, Kaj | Neurocomputing | 2018 | NA |
| 10.1016/j.paerosci.2018.10.001 | Quantification Of Model Uncertainty In Rans Simulations: A Review | Xiao, Heng, 0000-0002-3323-4028; Cinnella, Paola | Progress In Aerospace Sciences | 2019 | NA |
| 10.1017/jfm.2018.770 | Subgrid Modelling For Two-Dimensional Turbulence Using Neural Networks | Maulik, R.; San, O., 0000-0002-2241-4648; Rasheed, A.; Vedula, P. | Journal Of Fluid Mechanics | 2018 | NA |
| 10.1017/jfm.2018.872 | Deep Learning Of Vortex-Induced Vibrations | Raissi, Maziar, 0000-0002-8467-4568; Wang, Zhicheng, 0000-0002-5856-6459; Triantafyllou, Michael S., 0000-0002-4960-7060; Karniadakis, George Em | Journal Of Fluid Mechanics | 2018 | NA |
| 10.1017/jfm.2019.238 | Super-Resolution Reconstruction Of Turbulent Flows With Machine Learning | Fukami, Kai; Fukagata, Koji, 0000-0003-4805-238X; Taira, Kunihiko, 0000-0002-3762-8075 | Journal Of Fluid Mechanics | 2019 | TRUE |
| 10.1017/jfm.2019.62 | Artificial Neural Networks Trained Through Deep Reinforcement Learning Discover Control Strategies For Active Flow Control | Rabault, Jean, 0000-0002-7244-6592; Kuchta, Miroslav; Jensen, Atle; Reglade, Ulysse; Cerardi, Nicolas | Journal Of Fluid Mechanics | 2019 | NA |
| 10.1017/jfm.2019.700 | Data-Driven Prediction Of Unsteady Flow Over A Circular Cylinder Using Deep Learning | Lee, Sangseung, 0000-0001-7341-8289; You, Donghyun, 0000-0003-2470-5411 | Journal Of Fluid Mechanics | 2019 | NA |
| 10.1029/2018wr023528 | Mo, Shaoxing, 0000-0003-2831-4805; Zhu, Yinhao; Zabaras, Nicholas, 0000-0003-3144-8388; Shi, Xiaoqing, 0000-0002-5074-8856; Wu, Jichun, 0000-0001-9799-6745 | Water Resources Research | 2019 | NA | |
| 10.1029/2018wr024638 | Mo, Shaoxing, 0000-0003-2831-4805; Zabaras, Nicholas, 0000-0003-3144-8388; Shi, Xiaoqing, 0000-0002-5074-8856; Wu, Jichun, 0000-0001-9799-6745 | Water Resources Research | 2019 | NA | |
| 10.1063/1.5061693 | Machine Learning Methods For Turbulence Modeling In Subsonic Flows Around Airfoils | Zhu, Linyang; Zhang, Weiwei; Kou, Jiaqing, 0000-0002-0965-5404; Liu, Yilang | Physics Of Fluids | 2019 | NA |
| 10.1063/1.5094943 | Fast Flow Field Prediction Over Airfoils Using Deep Learning Approach | Sekar, Vinothkumar, 0000-0001-5734-550X; Khoo, Boo Cheong, 0000-0003-4710-4598 | Physics Of Fluids | 2019 | NA |
| 10.1063/1.5113494 | A Deep Learning Enabler For Nonintrusive Reduced Order Modeling Of Fluid Flows | Pawar, S., 0000-0001-7562-799X; Rahman, S. M., 0000-0003-0996-6883; Vaddireddy, H.; San, O., 0000-0002-2241-4648; Rasheed, A.; Vedula, P. | Physics Of Fluids | 2019 | NA |
| 10.1073/pnas.1718942115 | Solving High-Dimensional Partial Differential Equations Using Deep Learning | Han, Jiequn, 0000-0002-3553-7313; Jentzen, Arnulf; E, Weinan | Proceedings Of The National Academy Of Sciences | 2018 | NA |
| 10.1103/physrevfluids.3.074602 | Physics-Informed Machine Learning Approach For Augmenting Turbulence Models: A Comprehensive Framework | Wu, Jin-Long; Xiao, Heng; Paterson, Eric | Physical Review Fluids | 2018 | NA |
| 10.1103/physrevfluids.4.034602 | Predictive Large-Eddy-Simulation Wall Modeling Via Physics-Informed Neural Networks | Yang, X. I. A.; Zafar, S.; Wang, J.-X.; Xiao, H. | Physical Review Fluids | 2019 | NA |
| 10.1103/physrevfluids.4.054603 | Predictions Of Turbulent Shear Flows Using Deep Neural Networks | Srinivasan, P. A.; Guastoni, L.; Azizpour, H.; Schlatter, P.; Vinuesa, R. | Physical Review Fluids | 2019 | NA |
| 10.1103/physrevfluids.4.100501 | Perspective On Machine Learning For Advancing Fluid Mechanics | Brenner, M. P.; Eldredge, J. D.; Freund, J. B. | Physical Review Fluids | 2019 | NA |
| 10.1126/science.aaw4741 | Hidden Fluid Mechanics: Learning Velocity And Pressure Fields From Flow Visualizations | Raissi, Maziar, 0000-0002-8467-4568; Yazdani, Alireza, 0000-0002-0139-2080; Karniadakis, George Em, 0000-0002-9713-7120 | Science | 2020 | NA |
| 10.1137/18m1191944 | Data-Driven Identification Of Parametric Partial Differential Equations | Rudy, Samuel; Alla, Alessandro; Brunton, Steven L.; Kutz, J. Nathan | Siam Journal On Applied Dynamical Systems | 2019 | NA |
| 10.1137/18m1229845 | Fpinns: Fractional Physics-Informed Neural Networks | Pang, Guofei; Lu, Lu, 0000-0002-5476-5768; Karniadakis, George Em, 0000-0002-9713-7120 | Siam Journal On Scientific Computing | 2019 | NA |
| 10.1137/19m1274067 | Deepxde: A Deep Learning Library For Solving Differential Equations | Lu, Lu, 0000-0002-5476-5768; Meng, Xuhui; Mao, Zhiping; Karniadakis, George Em, 0000-0002-9713-7120 | Siam Review | 2021 | NA |
| 10.1146/annurev-fluid-010518-040547 | Turbulence Modeling In The Age Of Data | Duraisamy, Karthik; Iaccarino, Gianluca; Xiao, Heng | Annual Review Of Fluid Mechanics | 2019 | NA |
| 10.1146/annurev-fluid-010719-060214 | Machine Learning For Fluid Mechanics | Brunton, Steven L.; Noack, Bernd R.; Koumoutsakos, Petros | Annual Review Of Fluid Mechanics | 2020 | NA |
| 10.2514/1.j058462 | Modal Analysis Of Fluid Flows: Applications And Outlook | Taira, Kunihiko; Hemati, Maziar S.; Brunton, Steven L.; Sun, Yiyang; Duraisamy, Karthik; Bagheri, Shervin; Dawson, Scott T. M.; Yeh, Chi-An | Aiaa Journal | 2020 | NA |